Our research
We focus on applying engineering methods to problems in biomechanics with the goal of improving human health. In particular we aim to understand the underlying mechanisms of traumatic brain injury in order to better prevent and diagnose. We also research on the cerebral hemodynamics and the effect it can have on neurodegenerative diseases and stroke. We use an array of computational and experimental approaches including finite element modeling, magnetic resonance imaging and impact biomechanics.
We aim to understand the underlying mechanisms of brain trauma and concussions for better diagnostic and preventative technologies and faster recoveries, using a combination of wearable sensors, computational modeling, and multi-faceted neuroimaging.
We aim to understand the effects of stroke on cerebral hemodynamics and to predict tissue viability in Stroke patients. By employing medical imaging, patient-specific modeling, and smart biomedical devices, we provide critical information on stroke severity and tissue viability. We then use novel machine learning techniques to provide predictive metrics for clinical outcomes.
Elasticity imaging is a technique that discovers the spatial distribution of mechanical properties of tis- sue using deformation and force measurements under various loading conditions. We employ physics-informed deep machine learning to discover the hidden space-dependent distribution of mechanical properties of soft tissues.
